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Assessment of methane emissions from the U.S. oil and gas supply chain



Methane emissions from the U.S. oil and natural gas supply chain were estimated using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 Tg/y, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. EPA inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Significant emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.
Assessment of methane emissions
from the U.S. oil and gas supply chain
Ramón A. Alvarez
*, Daniel Zavala-Araiza
, David R. Lyon
, David T. Allen
Zachary R. Barkley
, Adam R. Brandt
, Kenneth J. Davis
, Scott C. Herndon
Daniel J. Jacob
, Anna Karion
, Eric A. Kort
, Brian K. Lamb
, Thomas Lauvaux
Joannes D. Maasakkers
, Anthony J. Marchese
, Mark Omara
, Stephen W. Pacala
Jeff Peischl
, Allen L. Robinson
, Paul B. Shepson
, Colm Sweeney
Amy Townsend-Small
, Steven C. Wofsy
, Steven P. Hamburg
Methane emissions from the U.S. oil and natural gas supply chain were estimated by
using ground-based, facility-scale measurements and validated with aircraft observations
in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our
facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year,
equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S.
Environmental Protection Agency inventory estimate, likely because existing inventory
methods miss emissions released during abnormal operating conditions. Methane
emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing
over a 20-year time horizon comparable to the CO
from natural gas combustion.
Substantial emission reductions are feasible through rapid detection of the root causes
of high emissions and deployment of less failure-prone systems.
Methane (CH
) is a potent greenhouse gas,
and CH
emissions from human activities
since preindustrial times are responsi-
ble for 0.97 W m
of radiative forcing,
as compared to 1.7 W m
for carbon
dioxide (CO
)(1). CH
is removed from the at-
mosphere much more rapidly than CO
; thus,
reducing CH
emissions can effectively reduce
the near-term rate of warming (2). Sharp growth
in U.S. oil and natural gas (O/NG) production
beginning around 2005 (3)raisedconcernsabout
the climate impacts of increased natural gas use
(4,5). By 2012, disagreement among published
estimates of CH
emissions from U.S. natural
gas operations led to a broad consensus that
additional data were needed to better charac-
terize emission rates (47). A large body of field
measurements made between 2012 and 2016
(table S1) has markedly improved understanding
of the sources and magnitude of CH
from the industrysoperations.Brandtet al.sum-
marized the early literature (8); other assessments
incorporated elements of recent data (911). This
work synthesizes recent studies to provide an
improved overall assessment of emissions from
the O/NG supply chain, which we define to in-
clude all operations associated with O/NG pro-
duction, processing, and transport (materials and
methods, section S1.0) (12).
Measurements of O/NG CH
emissions can
be classified as either top-down (TD) or bottom-
up (BU). TD studies quantify ambient methane
enhancements using aircraft, satellites, or tower
networks and infer aggregate emissions from all
contributing sources across large geographies.
TD estimates for nine O/NG production areas
have been reported to date (table S2). These
areas are distributed across the U.S. (fig. S1)
and account for ~33% of natural gas, ~24% of oil
production, and ~14% of all wells (13). Areas
sampled in TD studies also span the range of
hydrocarbon characteristics (predominantly gas,
predominantly oil, or mixed), as well as a range of
production characteristics such as well produc-
tivity and maturity. In contrast, BU studies gener-
ate regional, state, or national emission est im at es
by aggregating and extrapolating measured emis-
sions from individual pieces of equipment, oper-
ations, or facilities, using measurements made
directly at the emission point or, in the case of
facilities, directly downwind.
Recent BU studies have been performed on
equipment or facilities that are expected to rep-
resent the vast majority of emissions from the
O/NG supply chain (table S1). In this work, we
integrate the results of recent facility-scale BU
studies to estimate CH
emissions from the U.S.
O/NG supply chain, and then we validate the
results using TD studies (materials and meth-
ods). The probability distributions of our BU
methodology are based on observed facility-
level emissions, in contrast to the component-
by-component approach used for conventional
inventories. We thus capture enhancements pro-
duced by all sources within a facility, including
the heavy tail of the distribution. When the BU
estimate is developed in this manner, direct
comparison of BU and TD estimates of CH
emissions in the nine basins for which TD
measurements have been reported indicates
agreement between methods, within estimated
uncertainty ranges (Fig. 1).
Our national BU estimate of total CH
sions in 2015 from the U.S. O/NG supply chain
is 13 (+2.1/1.6, 95% confidence interval) Tg
/year (Table 1). This estimate of O/NG CH
emissions can also be expressed as a production-
normalized emission rate of 2.3% (+0.4%/0.3%)
by normalizing by annual gross natural gas pro-
duction [33 trillion cubic feet (13), with average
national BU emissions are from production,
gathering, and processing sources, which are
concentrated in active O/NG production areas.
Our assessment does not update emissions
from local distribution and end use of natural
gas, owing to insufficient information address-
ing this portion of the supply chain. However,
recent studies suggest that local distribution
emissions exceed the current inventory estimate
(1416), and that end-user emissions might also
be important. If these findings prove to be repre-
sentative, overall emissions from the natural gas
in Table 1 (materials and methods, section S1.5).
Our BU method and TD measurements yield
similar estimates of U.S. O/NG CH
in 2015, and both are significantly higher than
the corresponding estimate in the U.S. Environ-
mental Protection Agencys Greenhouse Gas
Inventory (EPA GHGI) (Table 1 and materials
and methods, section S1.3) (17). Discrepancies
between TD estimates and the EPA GHGI have
been reported previously (8,18). Our BU esti-
mate is 63% higher than the EPA GHGI, largely
due to a more than twofold difference in the
production segment (Table 1). The discrepancy
in production sector emissions alone is ~4 Tg
/year, an amount larger than the emissions
from any other O/NG supply chain segment.
Such a large difference cannot be attributed to
expected uncertainty in either estimate: The
extremal ends of the 95% confidence intervals
for each estimate differ by 20% (i.e., ~12 Tg/year
compared to ~10 Tg/year for the upper bound
of the EPA GHGI estimate).
We believe the reason for such large divergence
is that sampling methods underlying conven-
tional inventories systematically underestimate
total emissions because they miss high emis-
sions caused by abnormal operating conditions
(e.g., malfunctions). Distributions of measured
emissions from production sites in BU studies
are invariably tail-heavy,with large emission
rates measured at a small subset of sites at any
single point in time (1922). Consequently, the
most likely hypothesis for the difference be-
tween the EPA GHGI and BU estimates derived
from facility-level measurements is that measure-
ments used to develop GHGI emission factors
Alvarez et al., Science 361, 186188 (2018) 13 July 2018 1of3
Environmental Defense Fund, Austin, TX, USA.
of Texas at Austin, Austin, TX, USA.
The Pennsylvania
State University, University Park, PA, USA.
University, Stanford, CA, USA.
Aerodyne Research Inc.,
Billerica, MA, USA.
Harvard University, Cambridge, MA,
National Institute of Standards and Technology,
Gaithersburg, MD, USA.
University of Michigan, Ann
Arbor, MI, USA.
Washington State University, Pullman,
Colorado State University, Fort Collins, CO,
Princeton University, Princeton, NJ, USA.
University of Colorado, CIRES, Boulder, CO, USA.
Earth System Research Laboratory, Boulder, CO, USA.
Carnegie Mellon University, Pittsburgh, PA, USA.
Purdue University, West Lafayette, IN, USA.
of Cincinnati, Cincinnati, OH, USA.
*Corresponding author. Email:
on August 28, 2018 from
undersample abnormal operating conditions
encountered during the BU work. Component-
based inventory estimates like the GHGI have
been shown to underestimate facility-level emis-
sions (23), probably because of the technical
difficulty and safety and liability risks asso-
ciated with measuring large emissions from, for
example, venting tanks such as those observed
in aerial surveys (24).
Abnormal conditions causing high CH
sions have been observed in studies across the
O/NG supply chain. An analysis of site-scale emis-
sion measurements in the Barnett Shale con-
cluded that equipment behaving as designed
could not explain the number of high-emitting
production sites in the region (23). An extensive
aerial infrared camera survey of ~8000 pro-
duction sites in seven U.S. O/NG basins found
that ~4% of surveyed sites had one or more
observable highemission rate plumes (24)(de-
tection threshold of ~3 to 10 kg CH
/hour was
two to seven times higher than mean produc-
tion site emissions estimated in this work). Emis-
sions released from liquid storage tank hatches
and vents represented 90% of these sightings.
It appears that abnormal operating conditions
must be largely responsible, because the obser-
vation frequency was too high to be attributed
to routine operations like condensate flashing
or liquid unloadings alone (24). All other ob-
servations were due to anomalous venting from
dehydrators, separators, and flares. Notably, the
two largest sources of aggregate emissions in the
EPA GHGIpneumatic controllers and equip-
ment leakswere never observed from these
aerial surveys. Similarly, a national survey of
gathering facilities found that emission rates
were four times higher at the 20% of facilities
where substantial tank venting emissions were
observed, as compared to the 80% of facilities
without such venting (25). In addition, very large
emissions from leaking isolation valves at trans-
mission and storage facilities were quantified by
means of downwind measurement but could not
be accurately (or safely) measured by on-site
methods (26). There is an urgent need to com-
plete equipment-based measurement campaigns
that capture these large-emission events, so that
their causes are better understood.
In contrast to abnormal operational condi-
tions, alternative explanations such as outdated
component emission factors are unlikely to ex-
plain the magnitude of the difference between
our facility-based BU estimate and the GHGI.
First, an equipment-level inventory analogous
to the EPA GHGI but updated with recent di-
rect measurements of component emissions (ma-
terials and methods, section S1.4) predicts total
production emissions that are within ~10% of
the EPA GHGI, although the contributions of
individual source categories differ significant-
ly (table S3). Second, we consider unlikely an
alternative hypothesis that systematically higher
emissions during daytime sampling cause a
high bias in TD methods (materials and meth-
ods, section S1.6). Two other factors may lead
to low bias in EPA GHGI and similar inventory
estimates. Operator cooperation is required to
obtain site access for emission measurements
(8). Operators with lower-emitting sites are plau-
sibly more likely to cooperate in such studies,
and workers are likely to be more careful to
avoid errors or fix problems when measure-
ment teams are on site or about to arrive. The
potential bias due to this opt-instudy design
is very challenging to determine. We therefore
rely primarily on site-level, downwind mea-
surement methods with limited or no opera-
tor forewarning to construct our BU estimate.
Another possible source of bias is measurement
error. It has been suggested that malfunction of
a measurement instrument widely used in the
O/NG industry contributes to underestimated
emissions in inventories (27); however, this can-
not explain the more than twofold difference in
production emissions (28).
The tail-heavy distribution for many O/NG
emission sources has important implica-
tions for mitigation because it suggests that
most sourceswhether they represent whole
facilities or individual pieces of equipment
can have lower emissions when they operate as
designed. We anticipate that significant emis-
sions reductions could be achieved by deploying
well-designed emission detection and repair sys-
tems that are capable of identifying abnormally
operating facilities or equipment. For example,
pneumatic controllers and equipment leaks are
the largest emission sources in the O/NG pro-
duction segment exclusive of missing emission
sources (38 and 21%, respectively; table S3), with
malfunctioning controllers contributing 66% of
total pneumatic controller emissions (materials
and methods, section S1.4) and equipment leaks
60% higher than the GHGI estimate.
Alvarez et al., Science 361, 186188 (2018) 13 July 2018 2of3
Haynesville (7.7 bcf/d)
Barnett (5.9 bcf/d)
Northeast PA (5.8 bcf/d)
San Juan (2.8 bcf/d)
Fayetteville (2.5 bcf/d)
Bakken (1.9 bcf/d)
Uinta (1.2 bcf/d)
Weld County (1.0 bcf/d)
West Arkoma (0.37 bcf/d)
9-basin sum
9-basin sum, O/NG emissions (Mg CH4/h)
0 200 400 600-100% -50% 0% 50% 100% 150%
Fig. 1. Comparison of this works bottom-up (BU) estimates of methane emissions from oil
and natural gas (O/NG) sources to top-down (TD) estimates in nine U.S. O/NG production areas.
(A) Relative differences of the TD and BU mean emissions, normalized by the TD value, rank ordered
by natural gas production in billion cubic feet per day (bcf/d, where 1 bcf = 2.8 × 10
). Error
bars represent 95% confidence intervals. (B) Distributions of the nine-basin sum of TD and BU mean
estimates (blue and orange probability density, respectively). Neither the ensemble of TD-BU pairs
(A) nor the nine-basin sum of means (B) are statistically different [p= 0.13 by a randomization test,
and mean difference of 11% (95% confidence interval of 17 to 41%)].
Table 1. Summary of this works bottom-up estimates of CH
emissions from the U.S. oil and
natural gas (O/NG) supply chain (95% confidence interval) and comparison to the EPA
Greenhouse Gas Inventory (GHGI).
Industry segment
2015 CH
emissions (Tg/year)
This work (bottom-up) EPA GHGI (17)
Production 7.6 (+1.9/1.6) 3.5
................................... ................................... .................................. ..................................... .................................. .................................. ....
Gathering 2.6 (+0.59/0.18) 2.3
................................... ................................... .................................. ..................................... .................................. .................................. ....
Processing 0.72 (+0.20/0.071) 0.44
................................... ................................... .................................. ..................................... .................................. .................................. ....
Transmission and storage 1.8 (+0.35/0.22) 1.4
................................... ................................... .................................. ..................................... .................................. .................................. ....
Local distribution* 0.44 (+0.51/0.22) 0.44
................................... ................................... .................................. ..................................... .................................. .................................. ....
Oil refining and transportation* 0.034 (+0.050/0.008) 0.034
................................... ................................... .................................. ..................................... .................................. .................................. ....
U.S. O/NG total 13 (+2.1/1.7) 8.1 (+2.1/1.4)
................................... ................................... .................................. ..................................... .................................. .................................. ....
*This works emission estimates for these sources are taken directly from the GHGI. The local distribution
estimate is expected to be a lower bound on actual emissions and does not include losses downstream of
customer meters due to leaks or incomplete combustion (materials and methods, section S1.5).
The GHGI only reports industry-wide uncertainties.
on August 28, 2018 from
Gathering operations, which transport unpro-
cessed natural gas from production sites to pro-
cessing plants or transmission pipelines, produce
~20% of total O/NG supply chain CH
Until the publication of recent measurements
(29), these emissions were largely unaccounted
by the EPA GHGI. Gas processing, transmission
and storage together contribute another ~20%
of total O/NG supply chain emissions, most of
which come from ~2500 processing and com-
pression facilities.
Our estimate of emissions from the U.S. O/NG
supply chain (13 Tg CH
/year) compares to the
EPA estimate of 18 Tg CH
/year for all other
anthropogenic CH
sources (17). Natural gas
losses are a waste of a limited natural resource
(~$2 billion/year), increase global levels of sur-
face ozone pollution (30), and substantially erode
the potential climate benefits of natural gas use.
Indeed, our estimate of CH
emissions across
the supply chain, per unit of gas consumed, re-
sults in roughly the same radiative forcing as
does the CO
from combustion of natural gas
over a 20-year time horizon (31% over 100 years).
Moreover, the climate impact of 13 Tg CH
over a 20-year time horizon roughly equals that
from the annual CO
emissions from all U.S. coal-
fired power plants operating in 2015 (31% of the
impact over a 100-year time horizon) (materials
and methods, section S1.7).
We suggest that inventory methods would be
improved by including the substantial volume
of missing O/NG CH
emissions evident from
the large body of scientific work now available
and synthesized here. Such empirical adjustments
based on observed data have been previously used
in air quality management (31).
The large spatial and temporal variability in
emissions for similar equipment and fa-
cilities (due to equipment malfunction and other
abnormal operating conditions) reinforces the
conclusion that substantial emission reductions
are feasible. Key aspects of effective mitigation
include pairing well-established technologies
and best practices for routine emission sources
with economically viable systems to rapidly de-
tect the root causes of high emissions arising
from abnormal conditions. The latter could in-
volve combinations of current technologies such
as on-site leak surveys by company personnel
using optical gas imaging (32), deployment of
passive sensors at individual facilities (33,34)
or mounted on ground-based work trucks (35),
and in situ remote-sensing approaches using
tower networks, aircraft, or satellites (36). Over
time, the development of less failure-prone sys-
tems would be expected through repeated ob-
servation of and further research into common
causes of abnormal emissions, followed by re-
engineered design of individual components
and processes.
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The authors are grateful to R. Harriss for support in the design and
conduct of studies. We thank D. Zimmerle, A. Robertson, and
A. Pintar for helpful di scussions, and th e scores of researc hers
that contribute d to the body of work a ssessed here. Fu ndi ng:
Alfred P. Sloan Fou ndation, Fiona and Stan Druckenmiller,
Heising-Simon s Foundation, Bil l and Susan Oberndo rf, Betsy and
Sam Reeves, Robert son Foundatio n, TomKat Charita ble Trust,
and the Walton Family Foundation (for EDF authors as well as
support of related studies involving D.T.A, S.C.H., A.K., E.A.K.,
B.K.L., A.J.M., A.L.R., P.B.S., C.S., A.T.-S., S.C.W.); DOE National
Energy Technology Laboratory (Z.R.B., K.J.D., T.L., A.L.R.);
NASA Earth Science Division (D.J.J., E.A.K., J.D.M.); NOAA Climate
Program Office (E.A.K., J.P., A.L.R., C.S.). Author contributions:
R.A.A., D.Z-A., D.R.L., and S.P.H. conceived the study; R.A.A.,
D.Z-A., D.R.L., E.A.K., S.W.P. and S.P.H. designed the study and
interpreted results with input from all authors; each author
contributed to the collection , analysis, or assessment of one
or more datase ts necessary to perform this study; D.Z-A,
D.R.L, and S.W.P, performed the analysis, with contributions
from R.A.A., A.R.B., A.K., and M.O.; R.A.A., D.Z-A., D.R.L., S.W.P.,
S.C.W., and S.P.H. wrote the manuscript with input fr om all
authors. Competi ng interests: None declared. Data and
materials availa bility: All dat a and methods nee ded to
reproduce the re sults in the paper are provided in the paper or
as supplementar y materials. Add itional author d isclosures
(affiliations, funding sources, finan cial holdings) a re provided in
the supplementa ry materials.
Materials and Methods
Additional Author Disclosures
Figs. S1 to S11
Tables S1 to S12
References (3777)
Databases S1 and S2
19 December 2017; accepted 18 May 2018
Published online 21 June 2018
Alvarez et al., Science 361, 186188 (2018) 13 July 2018 3of3
on August 28, 2018 from
Assessment of methane emissions from the U.S. oil and gas supply chain
Sweeney, Amy Townsend-Small, Steven C. Wofsy and Steven P. Hamburg
Maasakkers, Anthony J. Marchese, Mark Omara, Stephen W. Pacala, Jeff Peischl, Allen L. Robinson, Paul B. Shepson, Colm
Davis, Scott C. Herndon, Daniel J. Jacob, Anna Karion, Eric A. Kort, Brian K. Lamb, Thomas Lauvaux, Joannes D.
Ramón A. Alvarez, Daniel Zavala-Araiza, David R. Lyon, David T. Allen, Zachary R. Barkley, Adam R. Brandt, Kenneth J.
originally published online June 21, 2018DOI: 10.1126/science.aar7204
(6398), 186-188.361Science
, this issue p. 186Science
better understanding of mitigation efforts outlined by the Paris Agreement.
methodology used to obtain them, could improve and verify international inventories of greenhouse gases and provide a
because current inventory methods miss emissions that occur during abnormal operating conditions. These data, and the
higher than the U.S. Environmental Protection Agency inventory estimate. They suggest that this discrepancy exists
60% reassessed the magnitude of this leakage and found that in 2015, supply chain emissions were et al.Alvarez
Considerable amounts of the greenhouse gas methane leak from the U.S. oil and natural gas supply chain.
A leaky endeavor
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on August 28, 2018 from
... Finally, accounting for methane emissions in climate assessments of clean hydrogen applications also suffers the same analytical challenges as hydrogen, given that it is also a short-lived gas commonly assessed through a long-term lens. The climate effects of methane emissions are often further underestimated, as natural gas leak rates are consistently un-derestimated in national emission inventories (Alvarez et al., 2018;Shen et al., 2021). Studies have shown that accounting for high methane emissions from upstream supply chains associated with blue hydrogen production when considered on shorter time horizons reveals near-term harm to the climate that is not conveyed with standard GWP-100 assessments (Howarth and Jacobson, 2021). ...
... For methane emission estimates (including venting, purging, and flaring) upstream of hydrogen production, we use a range of 1 % (best case) to 3 % (worst case) per unit methane consumed. This is based on the latest understanding of upstream natural gas leakage from oil and gas production as well as the distribution of natural gas (Alvarez et al., 2018). Table 2 shows the hydrogen and methane emissions used in this study for best-and worst-case leak rates based on 1 kg of either green or blue hydrogen deployed. ...
... However, the total amount of leakage in current hydrogen systems remains unknown, with the analytical capacity to accurately measure small levels of leakage in situ being largely unavailable. The lessons learned from extensive measurements of natural gas value-chain leaks over the last decade (similar infrastructure but larger molecule) have shown that leakage rates are far higher than expected (Alvarez et al., 2018). While hydrogen is arguably a more valuable product than natural gas, given the current cost of producing it, the lack of empirical measurements cannot confirm any assumptions regarding the influence of the cost of lost product on leakage rates, especially if there is no regulatory enforcement. ...
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Given the urgency to decarbonize global energy systems, governments and industry are moving ahead with efforts to increase deployment of hydrogen technologies, infrastructure, and applications at an unprecedented pace, including USD billions in national incentives and direct investments. While zero- and low-carbon hydrogen hold great promise to help solve some of the world's most pressing energy challenges, hydrogen is also an indirect greenhouse gas whose warming impact is both widely overlooked and underestimated. This is largely because hydrogen's atmospheric warming effects are short-lived – lasting only a couple decades – but standard methods for characterizing climate impacts of gases consider only the long-term effect from a one-time pulse of emissions. For gases whose impacts are short-lived, like hydrogen, this long-term framing masks a much stronger warming potency in the near to medium term. This is of concern because hydrogen is a small molecule known to easily leak into the atmosphere, and the total amount of emissions (e.g., leakage, venting, and purging) from existing hydrogen systems is unknown. Therefore, the effectiveness of hydrogen as a decarbonization strategy, especially over timescales of several decades, remains unclear. This paper evaluates the climate consequences of hydrogen emissions over all timescales by employing already published data to assess its potency as a climate forcer, evaluate the net warming impacts from replacing fossil fuel technologies with their clean hydrogen alternatives, and estimate temperature responses to projected levels of hydrogen demand. We use the standard global warming potential metric, given its acceptance to stakeholders, and incorporate newly published equations that more fully capture hydrogen's several indirect effects, but we consider the effects of constant rather than pulse emissions over multiple time horizons. We account for a plausible range of hydrogen emission rates and include methane emissions when hydrogen is produced via natural gas with carbon capture, usage, and storage (CCUS) (“blue” hydrogen) as opposed to renewables and water (“green” hydrogen). For the first time, we show the strong timescale dependence when evaluating the climate change mitigation potential of clean hydrogen alternatives, with the emission rate determining the scale of climate benefits or disbenefits. For example, green hydrogen applications with higher-end emission rates (10 %) may only cut climate impacts from fossil fuel technologies in half over the first 2 decades, which is far from the common perception that green hydrogen energy systems are climate neutral. However, over a 100-year period, climate impacts could be reduced by around 80 %. On the other hand, lower-end emissions (1 %) could yield limited impacts on the climate over all timescales. For blue hydrogen, associated methane emissions can make hydrogen applications worse for the climate than fossil fuel technologies for several decades if emissions are high for both gases; however, blue hydrogen yields climate benefits over a 100-year period. While more work is needed to evaluate the warming impact of hydrogen emissions for specific end-use cases and value-chain pathways, it is clear that hydrogen emissions matter for the climate and warrant further attention from scientists, industry, and governments. This is critical to informing where and how to deploy hydrogen effectively in the emerging decarbonized global economy.
... Since pre-industrial times, CH 4 mole fractions have risen by 150 % (Myhre et al., 2013) with the addition of anthropogenic sources identified as the cause of the rising abundance (Dean et al., 2018). CH 4 emissions can be apportioned between anthropogenic influences, such agriculture, waste management (Nisbet et al., 2016;Schaefer et al., 2016), and fossil fuel activities Alvarez et al., 2018), and natural sources which are dominated by wetlands (Bousquet et al., 2006(Bousquet et al., , 2011Schaefer et al., 2016). Though the major sources of atmospheric CH 4 have been identified, uncertainty in emission rates (Ehhalt et al., 2001;Lu et al., 2022) detrimentally affects our understanding of the total CH 4 burden and its subsequent climate impact (Nisbet et al., 2014). ...
... In situ measurements have been used extensively for quantifying methane emissions. Useful accuracy and precision have been achieved when measuring emissions from cities (Cui et al., 2015;McKain et al., 2015;Heimburger et al., 2017;Plant et al., 2019;, and oil and gas production basins (Alvarez et al., 2018;Barkley et al., 2019a), with an emerging ability to track emissions changes over time (Lyon et al., 2021;Lin et al., 2021). The in situ measurement density available for this quality of emissions quantification, however, is limited at present to a small number of intensive study areas (Richardson et al., 2017;Verhulst et al., 2017;Karion et al., 2020). ...
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The NASA Langley Research Center High Altitude Lidar Observatory (HALO) is a multi-functional and modular lidar developed to address the observational needs of NASA's weather, climate, carbon cycle, and atmospheric composition focus areas. HALO measures atmospheric H2O mixing ratios, CH4 mole fractions, and aerosol/cloud optical properties using the differential absorption lidar (DIAL) and high-spectral-resolution lidar (HSRL) techniques. In 2019 HALO participated in the NASA Atmospheric Carbon and Transport – America campaign on board the NASA C-130 to complement a suite of greenhouse gas in situ sensors and provide, for the first time, simultaneous measurements of column CH4 and aerosol/cloud profiles. HALO operated in 18 of 19 science flights where the DIAL and integrated path differential absorption (IPDA) lidar techniques at 1645 nm were used for column and multi-layer measurements of CH4 mole fractions, and the HSRL and backscatter techniques were used at 532 and 1064 nm, respectively, for retrievals of aerosol backscatter, extinction, depolarization, and mixing layer heights. In this paper we present HALO's measurement theory for the retrievals of column and multi-layer XCH4, retrieval accuracy, and precision including methods for bias correction and a comprehensive total column XCH4 validation comparison to in situ observations. Comparisons of HALO XCH4 to in situ-derived XCH4, collected during spiral ascents and descents, indicate a mean difference of 2.54 ppb and standard deviation (SD) of the differences of 16.66 ppb when employing 15 s along-track averaging (<3 km). A high correlation coefficient of R=0.9058 was observed for the 11 in situ spiral comparisons. Column XCH4 measured by HALO over regional scales covered by the ACT-America campaign is compared against in situ CH4 measurements carried out within the planetary boundary layer (PBL) from both the C-130 and B200 aircraft. Favorable correlation between the in situ point measurements within the PBL and the remote column measurements from HALO elucidates the sensitivity of a column-integrating lidar to CH4 variability within the PBL, where surface fluxes dominate the signal. Novel capabilities for CH4 profiling in regions of clear air using the DIAL technique are presented and validated for the first time. Additionally, profiling of CH4 is used to apportion the PBL absorption from the total column and is compared to previously reported IPDA cloud slicing techniques that estimate PBL columns using strong echoes from fair weather cumulus. The analysis presented here points towards HALO's ability to retrieve accurate and precise CH4 columns with the prospects for future multi-layer profiling in support of future suborbital campaigns.
... Uno studio di sintesi a livello di sito (Alvarez et al., 2018) ha suggerito che i metodi usati negli inventari non tengono conto delle emissioni rilasciate durante condizioni di funzionamento anomale, i cosiddetti super-emitters, una conclusione condivisa da altri studi (ad esempio, Brandt et al., 2014;Brandt et al., 2016). ...
... Another essential benefit is the use of waste biomass from agriculture [50], avoiding CH 4 emissions from manure and slurry (the global warming potential for CH 4 is 23). This has a more significant GHG reduction effect than just lowering CO 2 emissions [32,51,52]. The reduction of GHG emissions through biogas production depends on the type and structure of the feedstocks used. ...
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The importance of biogas in the energy mix in Poland and Latvia is very low. In Poland, 306 million m3 of biogas is produced annually, and in Latvia, 56 million m3. The share of energy from agricultural biogas in Latvia is 1.6%, and in Poland, only 0.12%. This study analyzed the impact of the structure on CO2 emissions from agricultural biogas production in Latvia and Poland. The emission was determined in accordance with the EU directive. The structure of substrates was dominated by those from the second generation, i.e., manure and food waste. In Latvia, it was 70%, and in Poland, 78%. The manure share was 45% and 24%, respectively. The anaerobic digestion of manure guarantees high GHG savings thanks to the avoided emissions from the traditional storage and management of raw manure as organic fertilizer. The level of emissions from the production of agricultural biogas was calculated for the variant with the use of closed digestate tanks, and it was about 10–11 g CO2/MJ, which is comparable to the emissions from solar photovoltaic sources. When using open tanks, the emission level was twice as high, but it was still many times less than from the Polish or Latvian energy mix. Such a low level of emissions resulted from the high share of manure. The level of emission reduction reached 90% compared to fossil fuels. The use of second-generation feedstock in biogas production provides environmental benefits. Therefore, if wastes are used in biogas generation, and the influence on the local environment and overall GHG emissions is positive, authorities should support such activity.
... Bottom-up inventories estimate emissions for offshore O&G production (and O&G more generally) by combining emission factors with activity data. While these bottom-up inventories are important for national scale accounting, many field measurements of onshore oil and gas infrastructure indicate significant discrepancies when compared with inventories (Brandt et al 2014, Zavala-Araiza et al 2015, Alvarez et al 2018. In some cases, emission factors from onshore oil and gas production are applied to offshore platforms or emissions factors from one type of offshore rig are applied uniformly to all offshore platforms. ...
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Offshore oil and natural gas platforms are responsible for about 30% of global oil and natural gas production. Despite the large share of global production there are few studies that have directly measured atmospheric methane emanating from these platforms. This study maps CH4 emissions from shallow water offshore oil and gas platforms with an imaging spectrometer by employing a method to capture the sun glint reflection from the water directly surrounding the target areas. We show how remote sensing with imaging spectrometers and glint targeting can be used to efficiently observe offshore infrastructure, quantify methane emissions, and attribute those emissions to specific infrastructure types. In 2021, the Global Airborne Observatory (GAO) platform, which is an aircraft equipped with a Visible Short-Wave InfraRed (VSWIR) imaging spectrometer, surveyed over 150 offshore platforms and surrounding infrastructure in US federal and state waters in the Gulf of Mexico representing ~ 8% of active shallow water infrastructure there. We find that CH4 emissions from the measured platforms exhibit highly skewed super emitter behavior. We find that these emissions mostly come from tanks and vent booms or stacks. We also find that the persistence and the loss rate from shallow water offshore infrastructure tends to be much higher than for typical onshore production.
... The task of this particular project was motivated by the rapid ongoing degradation of our ecosystem and the potential need for monitoring and localizing sources of greenhouse gas emissions. For example, the authors in [15] demonstrate the importance of finding methane leaks for holding oil and gas suppliers accountable and for identifying the causes of such leaks. Among other options, the authors suggest using aircraft for remote sensing. ...
Conference Paper
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This paper features a model for promoting Science, Technology, Engineering, and Mathematics (STEM) in the K-12 education level by developing teaching platforms together with university students. Usually, technical universities develop simulators and technologies as part of academic plans and research projects with students. For instance, in sessions of a university semester project, students often develop technical solutions useful for later use to promote STEM topics. We document experiences at TU Berlin where bachelor students developed a simulator using a drone for measuring CO 2 levels in the atmosphere. The topic was challenging enough to fulfill the research requirements at the university; at the same time, the resulting code provided the material to prepare teaching activities at the K-12 level. Using the publicly accessible code, we also elaborate on lesson plans and activities to apply this specific example at the K-12 level.
... They quote top down (atmospheric, aircraft, satellite) studies ranging from 0.2% to 17.3 %. Alvarez et al (Alvarez et al., 2018) estimate methane emission as 2.3% of gross US production. Heath et al (Heath et al., 2015) partition emissions by four main segments of the natural gas industry: ~33% production, ~14% processing, transmission and storage ~33% and distribution ~20%; and approximately 43% of total methane emissions from compressors. ...
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Hydrogen produced from natural gas with steam methane reforming coupled with carbon capture and sequestration (SMRCCS) is proposed as fuel for consumer heating and cooking systems. This paper presents estimates of the energy losses and methane and carbon dioxide emission and global warming across the whole gas to hydrogen heat supply chain – from production to consumer. Processed natural gas is typically about 95% methane which is a potent greenhouse gas with a global warming potential (GWP) such that, with 20 year and 100 year GWP horizons, about 4% and 8% leakage respectively will cause as much global warming as the carbon dioxide formed when burning the methane. Data on gas emissions and SMRCCS costs and performance are sparse and wide ranging and this presents a major problem in accurately appraising the possible role of hydrogen from methane. The survey indicates emissions between 50 and 200 gCO2eq per unit of heat (kWhth) for SMRCCS H2 heat depending on leakage and GWP time horizon assumed. The second part of the paper reviews gas supply pricing and security and presents a cost minimised configuration of a SMRCCS hydrogen heating system derived with a simple model. Uncertainty in SMRCCS greenhouse gas emissions coupled with a net zero emission target and the long term issue of the physical and economic security of natural gas supply, bear on the potential advantages of SMRCCS as compared to other options, such as heating with renewable electricity driving consumer or district heating heat pumps.
... However, fugitive and vented CH 4 creates environmental pollution problems and has a global warming potential 28-36 times of carbon dioxide on a 100 year horizon (Masson-Delmotte et al 2021). Research in different regions consistently shows current municipal, state, and national greenhouse gas (GHG) inventories underestimate the actual CH 4 emissions (Alvarez et al 2018, Sargent et al 2021, Tyner and Johnson 2021. The emission gaps could be attributed to under-characterized sources (Saint-Vincent and Pekney 2019), temporal variations in emission rates over time and intermittency (Vaughn et al 2018), non-ideal current inventory data input models (Rutherford et al 2021), and heavy-tailed emitters (Zavala-Araiza et al 2018). ...
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The 2015 Aliso Canyon storage well blowout was widely reported as the worst natural gas leak in U.S. history and released ~0.1 MMt (million metric tons) of methane (CH4), a potent greenhouse gas. Although storage well emissions are estimated in the U.S. Environmental Protection Agency's annual Greenhouse Gas Inventory, the inventory does not include historical estimates of anomalous large emission events other than Aliso Canyon. A total of 129 underground natural gas storage (UGS) incident-related events between 1940 and 2016 were compiled from various federal/state agencies and literature reviews. Incident emissions were estimated based on best available information, such as direct operator reports, the monetary cost of gas lost, or modeling of the escaping gas at sonic speeds. There are 388 active UGS fields in 3 types of reservoirs: salt caverns, aquifers, and depleted oil and gas fields. 53% of events were in the depleted oil and gas fields, which account for 79% of storage fields. Texas recorded the highest number of incidents (20), 14 of which were in salt dome reservoirs. The incident emissions showed a heavy-tailed emission pattern with CH4 releases up to 29 billion cubic feet (Bcf) (8.2 × 10 ⁸ m ³ ). The top 7 events contributed 98% of the total estimated/measured CH4 emissions.
... The age and level of maintenance at gas extraction, processing, transport, and storage facilities is a key factor in the environmental impact of natural gas [190][191][192]. 'Super emitters' utilising dated, inefficient or poorly maintained equipment bear responsibility for a larger share of the environmental impact of natural gas, with the largest GHG emission source-methane venting and leakage during gas recovery-able to be reduced by 75-99% using modern equipment [191][192][193][194]. Methane emissions associated with shale gas production can be equal to [195] or disproportionally (30-90%) higher [190,196] than conventional gas due to methane emissions resulting from flow-back fluids and drilling operations. ...
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Immediate and widespread changes in energy generation and use are critical to safeguard our future on this planet. However, while the necessity of renewable electricity generation is clear, the aviation, transport and mobility, chemical and material sectors are challenging to fully electrify. The age-old Fischer-Tropsch process and natural gas industry could be the bridging solution needed to accelerate the energy revolution in these sectors – temporarily powering obsolete vehicles, acting as renewable energy’s battery, supporting expansion of hydrogen fuel cell technologies and the agricultural and waste sectors as they struggle to keep up with a full switch to biofuels. Natural gas can be converted into hydrogen, synthetic natural gas, or heat during periods of low electricity demand and converted back to electricity again when needed. Moving methane through existing networks and converting it to hydrogen on-site at tanking stations also overcomes hydrogen distribution, storage problems and infrastructure deficiencies. Useful co-products include carbon nanotubes, a valuable engineering material, that offset emissions in the carbon nanotube and black industries. Finally, excess carbon can be converted back into syngas if desired. This flexibility and the compatibility of natural gas with both existing and future technologies provides a unique opportunity to rapidly decarbonise sectors struggling with complex requirements.
As atmospheric methane concentrations increase at record pace, it is critical to identify individual emission sources with high potential for mitigation. Here, we leverage the synergy between satellite instruments with different spatiotemporal coverage and resolution to detect and quantify emissions from individual landfills. We use the global surveying Tropospheric Monitoring Instrument (TROPOMI) to identify large emission hot spots and then zoom in with high-resolution target-mode observations from the GHGSat instrument suite to identify the responsible facilities and characterize their emissions. Using this approach, we detect and analyze strongly emitting landfills (3 to 29 t hour-1) in Buenos Aires, Delhi, Lahore, and Mumbai. Using TROPOMI data in an inversion, we find that city-level emissions are 1.4 to 2.6 times larger than reported in commonly used emission inventories and that the landfills contribute 6 to 50% of those emissions. Our work demonstrates how complementary satellites enable global detection, identification, and monitoring of methane superemitters at the facility level.
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Natural gas infrastructure releases methane (CH4), a potent greenhouse gas, into the atmosphere. The estimated emission rate associated with the production and transportation of natural gas is uncertain, hindering our understanding of its greenhouse footprint. This study presents a new application of inverse methodology for estimating regional emission rates from natural gas production and gathering facilities in north-eastern Pennsylvania. An inventory of CH4 emissions was compiled for major sources in Pennsylvania. This inventory served as input emission data for the Weather Research and Forecasting model with chemistry enabled (WRF-Chem), and atmospheric CH4 mole fraction fields were generated at 3 km resolution. Simulated atmospheric CH4 enhancements from WRF-Chem were compared to observations obtained from a 3-week flight campaign in May 2015. Modelled enhancements from sources not associated with upstream natural gas processes were assumed constant and known and therefore removed from the optimization procedure, creating a set of observed enhancements from natural gas only. Simulated emission rates from unconventional production were then adjusted to minimize the mismatch between aircraft observations and model-simulated mole fractions for 10 flights. To evaluate the method, an aircraft mass balance calculation was performed for four flights where conditions permitted its use. Using the model optimization approach, the weighted mean emission rate from unconventional natural gas production and gathering facilities in north-eastern Pennsylvania approach is found to be 0.36 % of total gas production, with a 2σ confidence interval between 0.27 and 0.45 % of production. Similarly, the mean emission estimates using the aircraft mass balance approach are calculated to be 0.40 % of regional natural gas production, with a 2σ confidence interval between 0.08 and 0.72 % of production. These emission rates as a percent of production are lower than rates found in any other basin using a top-down methodology, and may be indicative of some characteristics of the basin that make sources from the north-eastern Marcellus region unique.
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A synthesis of new methane (CH4) emission data from a recent series of ground-based field measurements shows that 1.7% of the methane in natural gas is emitted between extraction and delivery (with a 95% confidence interval from 1.3% to 2.2%). This synthesis was made possible by a recent series of methane emission measurement campaigns that focused on the natural gas supply chain, production through distribution. The new data were translated to a standard basis, augmented with other data sources as needed, and simulated using a Monte Carlo-enabled, life cycle model. Gathering facilities and production pneumatics are the top methane emission reduction opportunities for the natural gas sector, but there are knowledge gaps and sources of uncertainty that merit further research. In particular, “unassigned” emissions that were measured at the site level, as opposed to component-level emissions measured directly at the device level, account for 19% of supply chain methane emissions. By definition, unassigned emissions cannot be attributed to specific emission sources, and the current data do not provide insight into how they vary geographically. The inclusion of unassigned emissions makes the bottom-up compilation of emission sources more complete, but is a source of uncertainty that points to opportunities for further research. Further research should include geographically diverse measurement studies that provide a better understanding of regional variability and validate emission measurements by using a combination of component- and site-level measurements.
Large CH4 leak rates have been observed in the Uintah Basin of eastern Utah, an area with over 10,000 active and producing natural gas and oil wells. In this paper, we model CH4 concentrations at four sites in the Uintah Basin and compare the simulated results to in situ observations at these sites during two spring time periods in 2015 and 2016. These sites include a baseline location (Fruitland), two sites near oil wells (Roosevelt and Castlepeak), and a site near natural gas wells (Horsepool). To interpret these measurements and relate observed CH4 variations to emissions, we carried out atmospheric simulations using the Stochastic Time-Inverted Lagrangian Transport model driven by meteorological fields simulated by the Weather Research and Forecasting and High Resolution Rapid Refresh models. These simulations were combined with two different emission inventories: (1) aircraft-derived basin-wide emissions allocated spatially using oil and gas well locations, from the National Oceanic and Atmospheric Administration (NOAA), and (2) a bottom-up inventory for the entire U.S., from the Environmental Protection Agency (EPA). At both Horsepool and Castlepeak, the diurnal cycle of modeled CH4 concentrations was captured using NOAA emission estimates but was underestimated using the EPA inventory. These findings corroborate emission estimates from the NOAA inventory, based on daytime mass balance estimates, and provide additional support for a suggested leak rate from the Uintah Basin that is higher than most other regions with natural gas and oil development.
Methane emissions from oil and gas facilities can exhibit operation-dependent temporal variability; however, this variability has yet to be fully characterized. A field campaign was conducted in June 2014 in the Eagle Ford basin, Texas, to examine spatiotemporal variability of methane emissions using four methods. Clusters of methane-emitting sources were estimated from 14 aerial surveys of two (“East” or “West”) 35 × 35 km grids, two aircraft-based mass balance methods measured emissions repeatedly at five gathering facilities and three flares, and emitting equipment source-types were identified via helicopter-based infrared camera at 13 production and gathering facilities. Significant daily variability was observed in the location, number (East: 44 ± 20% relative standard deviation (RSD), N = 7; West: 37 ± 30% RSD, N = 7), and emission rates (36% of repeat measurements deviate from mean emissions by at least ±50%) of clusters of emitting sources. Emission rates of high emitters varied from 150–250 to 880–1470 kg/h and regional aggregate emissions of large sources (>15 kg/h) varied up to a factor of ∼3 between surveys. The aircraft-based mass balance results revealed comparable variability. Equipment source-type changed between surveys and alterations in operational-mode significantly influenced emissions. Results indicate that understanding temporal emission variability will promote improved mitigation strategies and additional analysis is needed to fully characterize its causes.
Atmospheric methane emissions from active natural gas production sites in normal operation were quantified using an inverse Gaussian method (EPA’s OTM 33a) in four major U.S. basins/plays: Upper Green River (UGR, Wyoming), Denver-Julesburg (DJ, Colorado), Uintah (Utah), and Fayetteville (FV, Arkansas). In DJ, Uintah, and FV, 72 – 83% of total measured emissions were from 20% of the well pads, while in UGR the highest 20% of emitting well pads only contributed 54% of total emissions. The total mass of methane emitted as a percent of gross methane produced, termed throughput-normalized methane average (TNMA) and determined by bootstrapping measurements from each basin, varied widely between basins and was (95% CI): 0.09% (0.05 – 0.15%) in FV, 0.18% (0.12 – 0.29%) in UGR, 2.1% (1.1 – 3.9%) in DJ, and 2.8% (1.0 – 8.6%) in Uintah. Overall, wet-gas basins (UGR, DJ, Uintah) had higher TNMA emissions than the dry-gas FV at all ranges of production per well pad. Among wet basins, TNMA emissions had a strong negative correlation with average gas production per well pad, suggesting that consolidation of operations onto single pads may reduce normalized emissions (average number of wells per pad is 5.3 in UGR versus 1.3 in Uintah and 2.8 in DJ).
Divergence in recent oil and gas related methane emission estimates between aircraft studies (basin total for a midday window) and emissions inventories (annualized regional and national statistics) indicate the need for better understanding the experimental design, including temporal and spatial alignment and interpretation of results. Our aircraft based methane emission estimates in a major US shale gas basin resolved from West to East show (i) similar spatial distributions for two days, (ii) strong spatial correlations with reported NG production (R(2)=0.75) and active gas well pad count (R(2)=0.81), and (iii) 2x higher emissions in the Western half (normalized by gas production) despite relatively homogeneous dry gas and well characteristics. Operator reported hourly activity data show that midday episodic emissions from manual liquid unloadings (a routine operation in this basin and elsewhere) could explain ~1/3 of the total emissions detected midday by the aircraft and ~2/3 of the West-East difference in emissions. The 22% emission difference between both days further emphasizes that episodic sources can substantially impact midday methane emissions and that aircraft may detect daily peak emissions rather than daily averages that are generally employed in emissions inventories. While the aircraft approach is valid, quantitative and independent, our study sheds new light on the interpretation of previous basin scale aircraft studies, and provides an improved mechanistic understanding of oil and gas related methane emissions.
Methane (CH4) is a potent greenhouse gas and the primary component of natural gas. The San Juan Basin (SJB) is one of the largest coal-bed methane producing regions in North America and, including gas production from conventional and shale sources, contributes ~2% of U.S. natural gas production in 2015. In this work, we quantify the CH4 flux from the SJB using continuous atmospheric sampling from aircraft collected during the TOPDOWN2015 field campaign in April 2015. Using five independent days of measurements and the aircraft-based mass balance method, we calculate an average CH4 flux of 0.54 ± 0.20 Tg yr-1 (1σ), in close agreement with the previous space-based estimate made for 2003-2009. These results agree within error with the US EPA gridded inventory for 2012. These flights combined with the previous satellite study suggests CH4 emissions have not changed. While there have been significant declines in natural gas production between measurements, recent increases in oil production in the SJB may explain why emission of CH4 has not declined. Airborne quantification of outcrops where seepage occurs are consistent with ground-based studies that indicate these geological sources are a small fraction of the basin total (0.02-0.12 Tg yr-1) and cannot explain basin-wide consistent emissions from 2003-2015.
Incomplete combustion during flaring can lead to production of black carbon (BC) and loss of methane and other pollutants to the atmosphere, impacting climate and air quality. However, few studies have measured flare efficiency in a real-world setting. We use airborne data of plume samples from 37 unique flares in the Bakken region of North Dakota in May 2014 to calculate emission factors for BC, methane, ethane, and combustion efficiency for methane and ethane. We find no clear relationship between emission factors and aircraft-level wind speed, nor between methane and BC emission factors. Observed median combustion efficiencies for methane and ethane are close to expected values for typical flares according to the US EPA (98%). However, we find that the efficiency distribution is skewed, exhibiting lognormal behavior. This suggests incomplete combustion from flares contributes almost 1/5 of the total field emissions of methane and ethane measured in the Bakken shale, more than double the expected value if 98\% efficiency was representative. BC emission factors also have a skewed distribution, but we find lower emission values than previous studies. The direct observation for the first time of a heavy-tail emissions distribution from flares suggests the need to consider skewed distributions when assessing flare impacts globally.
Presently, there is high uncertainty in estimates of methane (CH4) emissions from natural gas-fired power plants (NGPP) and oil refineries, two major end users of natural gas. Therefore, we measured CH4 and CO2 emissions at three NGPPs and three refineries using an aircraft-based mass balance technique. Average CH4 emission rates (NGPPs: 140±70 kg/hr; refineries: 580±220 kg/hr, 95% CL) were larger than facility-reported estimates by factors of 21-120 (NGPPs) and 11-90 (refineries). At NGPPs, the percentage of unburned CH4 emitted from stacks (0.01-0.14%) was much lower than respective facility-scale losses (0.10-0.42%), and CH4 emissions from both NGPPs and refineries were more strongly correlated with enhanced H2O concentrations R(2)avg=0.65) than with CO2 (R(2)avg=0.21), suggesting non-combustion-related equipment as potential CH4 sources. Additionally, calculated throughput-based emission factors (EF) derived from the NGPP measurements made in this study were, on average, a factor of 4.4 (stacks) and 42 (facility-scale) larger than industry-used EFs. Subsequently, throughput-based EFs for both the NGPPs and refineries were used to estimate total U.S. emissions from these facility-types. Results indicate that NGPPs and oil refineries may be large sources of CH4 emissions and could contribute significantly (1.5±0.8 Tg CH4/yr, 95% CL) to U.S. emissions.
The Marcellus Shale is a rapidly developing unconventional natural gas resource found in part of the Appalachian region. Air quality and climate concerns have been raised regarding development of unconventional natural gas resources. Two ground-based mobile measurement campaigns were conducted to assess the impact of Marcellus Shale natural gas development on local scale atmospheric background concentrations of air pollution and climate relevant pollutants in Pennsylvania. The first campaign took place in Northeastern and Southwestern PA in the summer of 2012. Compounds monitored included methane (CH4), ethane, carbon monoxide (CO), nitrogen dioxide, and Proton Transfer Reaction Mass Spectrometer (PTR-MS) measured volatile organic compounds (VOC) including oxygenated and aromatic VOC. The second campaign took place in Northeastern PA in the summer of 2015. The mobile monitoring data were analyzed using interval percentile smoothing to remove bias from local unmixed emissions to isolate local-scale background concentrations. Comparisons were made to other ambient monitoring in the Marcellus region including a NOAA SENEX flight in 2013. Local background CH4 mole fractions were 140 ppbv greater in Southwestern PA compared to Northeastern PA in 2012 and background CH4 increased 100 ppbv from 2012 to 2015. CH4 local background mole fractions were not found to have a detectable relationship between well density or production rates in either region. In Northeastern PA, CO was observed to decrease 75 ppbv over the three year period. Toluene to benzene ratios in both study regions were found to be most similar to aged rural air masses indicating that the emission of aromatic VOC from Marcellus Shale activity may not be significantly impacting local background concentrations. In addition to understanding local background concentrations the ground-based mobile measurements were useful for investigating the composition of natural gas emissions in the region.